High-Speed Downlink Packet Access (HSDPA) is an enhanced 3G (third generation) mobile telephony communication protocol in the High-Speed Packet Access (HSPA) family. HSDPA uses both fast link adaptation and fast user scheduling for enabling very high data rates. Both techniques require the UE (use equipment) to feedback information to a Node B base station relating to the quality of the downlink channel observed by the UE. Typically, the UE determines the feedback information by estimating SINR (signal to interference-plus-noise ratio) on the downlink common pilot channel (CPICH) and then converting this to a channel quality indicator (CQI) using a look-up table. The look-up table contains a mapping of SINR to transport format (e.g., modulation type, coding rate, number of codes) and is defined in 3GPP TS 25.214, “Physical Layer Procedures (FDD),” Version 7.9.0, Release 7, July 2008.
For single-antenna systems, SINR is typically estimated using a CPICH-based approach as follows. First, a set of combining weights (e.g., Rake, G-Rake) appropriate for demodulation of the HS-DSCH (High Speed Downlink Shared Channel) is formulated. The combining weights are typically denoted by a vector w. Next, the common pilot is despread using the same finger placements (e.g., Rake fingers, G-Rake fingers, etc.) as used to formulate the combining weights. The sequence of despread vectors during a single slot is given by:y(i)=hcp(i)+x(i), i=1 . . . K  (1)where i indexes the K CPICH symbols transmitted during the time slot (K=10). Here
            c      p        ⁡          (      i      )        =            1              2              ⁢          (              i        +        j            )      is a QPSK modulated pilot symbol known to the UE, h is the net channel response, and x(i) is a (zero mean) impairment vector consisting of interference and noise, referred to hereinafter as simply noise. The noise covariance is denoted Rx.
The combined CPICH despread values are given by:
                                                                        z                ⁡                                  (                  i                  )                                            =                            ⁢                                                w                  H                                ⁢                                  y                  ⁡                                      (                    i                    )                                                                                                                          =                            ⁢                                                                    w                    H                                    ⁢                  h                  ⁢                                                                          ⁢                                                            c                      p                                        ⁡                                          (                      i                      )                                                                      +                                                      w                    H                                    ⁢                                      x                    ⁡                                          (                      i                      )                                                                                                                              (        2        )            The first term in the expression of equation (2) is the desired signal component which has power given by the mean-squared value:Psig=E[|wHhcp(i)|2]=|wHh|2  (3)The second term in the expression of equation (2) is a noise component which has power given by the variance:Pnoise=E[wHx(i)xH(i)w]=wHRxw  (4)
The true SINR value at the output of the combiner conditioned on the combining weights w is thus given by:
                              SINR          true                =                                            P              sig                                      P              noise                                =                                                                                                          w                    H                                    ⁢                  h                                                            2                                                      w                H                            ⁢                              R                x                            ⁢              w                                                          (        5        )            
The true SINR is a hypothetical value which is not typically computed at the receiver in practice, since the receiver only has available estimates of the net channel response h and the noise covariance Rx, not the true values themselves. The SINR can be estimated, however, using estimates ĥ and {circumflex over (R)}x of the net channel response and noise covariance, respectively. Unbiased estimates are typically determined from the despread CPICH as follows:
                              h          ^                =                              1            K                    ⁢                                    ∑                              i                =                1                            10                        ⁢                                                            y                  p                                ⁡                                  (                  i                  )                                            ⁢                                                c                  p                  *                                ⁡                                  (                  i                  )                                                                                        (        6        )                        and                                                                            R            ^                    x                =                              1                          K              -              1                                ⁢                                    ∑                              i                =                1                            10                        ⁢                                                            [                                                                                    y                        ⁡                                                  (                          i                          )                                                                    ⁢                                                                        c                          p                          *                                                ⁡                                                  (                          i                          )                                                                                      -                                          h                      ^                                                        ]                                ⁡                                  [                                                                                    y                        ⁡                                                  (                          i                          )                                                                    ⁢                                                                        c                          p                          *                                                ⁡                                                  (                          i                          )                                                                                      -                                          h                      ^                                                        ]                                            H                                                          (        7        )            An unbiased estimate of the signal power is then typically obtained as:
                                          P            ^                    sig                =                                                                                            w                  H                                ⁢                                  h                  ^                                                                    2                    -                                    1              K                        ⁢                          w              H                        ⁢                                          R                ^                            x                        ⁢            w                                              (        8        )            and an unbiased estimate of the noise power as:{circumflex over (P)}noise=wH{circumflex over (R)}xw  (9)
The subtractive term in the expression of equation (8) is responsible for removing bias in the signal power estimate that occurs due to noise in the estimate of the net response. Smoothing of the signal and noise power is typically performed over a number of slots resulting in the SINR estimate:
                                          SINR            est                    =                                    〈                                                P                  ^                                sig                            〉                                      〈                                                P                  ^                                noise                            〉                                      ,                            (        10        )            where the operator - indicates a time average (i.e. smoothing). The SINR estimate is then mapped to a CQI value and fed back on the uplink HS-DPCCH (High Speed Dedicated Physical Control Channel) to inform the Node B of the downlink channel quality.
Notably, the SINR estimate is implicitly scaled by the power allocated to the CPICH channel since the despread CPICH is used to estimate all quantities. However, to make reliable link adaptation and scheduling decisions, the Node B requires an estimate of the SINR that would be experienced on the HS-DSCH (data) channel. The data and pilot SINRs are related by a scale factor that is a function of the data-to-pilot power ratio which is known by the Node B, and the ratio of the spreading factors on the data and pilot channels which is also known by the Node B. Hence, the Node B can apply the known scale factor to convert the pilot SINR to a corresponding data SINR.
The conventional SINR estimation approach described above is completely non-parametric. That is, the CPICH is used to measure the SINR and thus takes into account the instantaneous intra-cell interference, inter-cell interference, noise, RF impairments, etc. without explicitly modeling them. However, the purely non-parametric CPICH-based SINR estimation technique described above is not well suited for multi-antenna systems.
MIMO systems (multiple-input, multiple-output) use multiple antennas at both the transmitter and receiver for improving communication performance. For example, a 2×2 MIMO system has been standardized for Rel-7 HSDPA. The standardized 2×2 MIMO scheme in Rel-7 HSDPA is referred to as Dual-Transmit-Adaptive-Arrays (D-TxAA). D-TxAA can be viewed as an extension of a previously standardized transmit diversity scheme called Closed-Loop Mode-1 (CL-1), in that precoding vectors used for each data stream are drawn from the same codebook as used for CL-1. In contrast to CL-1; however, D-TxAA has two modes of operation: single-stream mode and dual-stream. In single-stream mode, one of four possible precoding vectors from the CL-1 codebook is applied to a single data stream. In dual-stream mode, one of two possible orthogonal pairs of precoding vectors are applied to two different data streams. In the case of dual-stream transmission, the same set of channelization codes is used for each data stream.
Several problems exist with the conventional CPICH based SINR estimation approach described above when applied to MIMO systems. First, and most significant, is the additional interference created by the reuse of spreading codes on the HS-DSCH (data) channel when in dual-stream mode. Such so-called code-reuse interference does not exist on the CPICH (pilot) channel since the pilots transmitted on each antenna are orthogonal. Hence use of the conventional CPICH-based SINR estimation approach described above yields an over-estimate of data channel quality leading to excessively high block error rates and thus significantly reduced throughput. In addition, precoding is used on the HS-DSCH whereas no precoding is used on the CPICH. Precoding also affects SINR, hence SINR values calculated using the conventional CPICH-based SINR estimation approach described above yields an even more inaccurate representation of the data channel quality since precoding is not employed on the pilot channel upon which SINR is solely derived.